{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Medical Image Classification Tutorial with the MedNIST Dataset\n",
    "\n",
    "In this tutorial, we introduce an end-to-end training and evaluation example based on the MedNIST dataset.\n",
    "\n",
    "We'll go through the following steps:\n",
    "* Create a dataset for training and testing\n",
    "* Use MONAI transforms to pre-process data\n",
    "* Use the DenseNet from MONAI for classification\n",
    "* Train the model with a PyTorch program\n",
    "* Evaluate on test dataset\n",
    "\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Project-MONAI/MONAI/blob/master/examples/notebooks/mednist_tutorial.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "%pip install -qU \"monai[pillow]\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "%pip install -qU matplotlib\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "MONAI version: 0.2.0\nPython version: 3.7.5 (default, Nov  7 2019, 10:50:52)  [GCC 8.3.0]\nNumpy version: 1.19.1\nPytorch version: 1.6.0\n\nOptional dependencies:\nPytorch Ignite version: NOT INSTALLED or UNKNOWN VERSION.\nNibabel version: NOT INSTALLED or UNKNOWN VERSION.\nscikit-image version: NOT INSTALLED or UNKNOWN VERSION.\nPillow version: 7.2.0\nTensorboard version: NOT INSTALLED or UNKNOWN VERSION.\n\nFor details about installing the optional dependencies, please visit:\n    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n\n"
    }
   ],
   "source": [
    "# Copyright 2020 MONAI Consortium\n",
    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "# you may not use this file except in compliance with the License.\n",
    "# You may obtain a copy of the License at\n",
    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
    "# Unless required by applicable law or agreed to in writing, software\n",
    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "# See the License for the specific language governing permissions and\n",
    "# limitations under the License.\n",
    "\n",
    "import os\n",
    "import shutil\n",
    "import tempfile\n",
    "\n",
    "import IPython\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import PIL\n",
    "import torch\n",
    "\n",
    "from monai.apps import download_and_extract\n",
    "from monai.config import print_config\n",
    "from monai.metrics import compute_roc_auc\n",
    "from monai.networks.nets import densenet121\n",
    "from monai.transforms import (\n",
    "    AddChannel,\n",
    "    Compose,\n",
    "    LoadPNG,\n",
    "    RandFlip,\n",
    "    RandRotate,\n",
    "    RandZoom,\n",
    "    ScaleIntensity,\n",
    "    ToTensor,\n",
    ")\n",
    "from monai.utils import set_determinism\n",
    "\n",
    "print_config()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup data directory\n",
    "\n",
    "You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable.  \n",
    "This allows you to save results and reuse downloads.  \n",
    "If not specified a temporary directory will be used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "/home/bengorman/notebooks/\n"
    }
   ],
   "source": [
    "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
    "root_dir = tempfile.mkdtemp() if directory is None else directory\n",
    "print(root_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download dataset\n",
    "\n",
    "The MedNIST dataset was gathered from several sets from [TCIA](https://wiki.cancerimagingarchive.net/display/Public/Data+Usage+Policies+and+Restrictions),\n",
    "[the RSNA Bone Age Challenge](http://rsnachallenges.cloudapp.net/competitions/4),\n",
    "and [the NIH Chest X-ray dataset](https://cloud.google.com/healthcare/docs/resources/public-datasets/nih-chest).\n",
    "\n",
    "The dataset is kindly made available by [Dr. Bradley J. Erickson M.D., Ph.D.](https://www.mayo.edu/research/labs/radiology-informatics/overview) (Department of Radiology, Mayo Clinic)\n",
    "under the Creative Commons [CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/).\n",
    "\n",
    "If you use the MedNIST dataset, please acknowledge the source."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "file /home/bengorman/notebooks/MedNIST.tar.gz exists, skip downloading.\nextracted file /home/bengorman/notebooks/MedNIST exists, skip extracting.\n"
    }
   ],
   "source": [
    "resource = \"https://www.dropbox.com/s/5wwskxctvcxiuea/MedNIST.tar.gz?dl=1\"\n",
    "md5 = \"0bc7306e7427e00ad1c5526a6677552d\"\n",
    "\n",
    "compressed_file = os.path.join(root_dir, \"MedNIST.tar.gz\")\n",
    "data_dir = os.path.join(root_dir, \"MedNIST\")\n",
    "\n",
    "download_and_extract(resource, compressed_file, root_dir, md5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set deterministic training for reproducibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "set_determinism(seed=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read image filenames from the dataset folders\n",
    "\n",
    "First of all, check the dataset files and show some statistics.  \n",
    "There are 6 folders in the dataset: Hand, AbdomenCT, CXR, ChestCT, BreastMRI, HeadCT,  \n",
    "which should be used as the labels to train our classification model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Total image count: 58954\nImage dimensions: 64 x 64\nLabel names: ['AbdomenCT', 'BreastMRI', 'CXR', 'ChestCT', 'Hand', 'HeadCT']\nLabel counts: [10000, 8954, 10000, 10000, 10000, 10000]\n"
    }
   ],
   "source": [
    "class_names = sorted(x for x in os.listdir(data_dir) if os.path.isdir(os.path.join(data_dir, x)))\n",
    "num_class = len(class_names)\n",
    "image_files = [\n",
    "    [\n",
    "        os.path.join(data_dir, class_names[i], x)\n",
    "        for x in os.listdir(os.path.join(data_dir, class_names[i]))\n",
    "    ]\n",
    "    for i in range(num_class)\n",
    "]\n",
    "num_each = [len(image_files[i]) for i in range(num_class)]\n",
    "image_files_list = []\n",
    "image_class = []\n",
    "for i in range(num_class):\n",
    "    image_files_list.extend(image_files[i])\n",
    "    image_class.extend([i] * num_each[i])\n",
    "num_total = len(image_class)\n",
    "image_width, image_height = PIL.Image.open(image_files_list[0]).size\n",
    "\n",
    "print(f\"Total image count: {num_total}\")\n",
    "print(f\"Image dimensions: {image_width} x {image_height}\")\n",
    "print(f\"Label names: {class_names}\")\n",
    "print(f\"Label counts: {num_each}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Randomly pick images from the dataset to visualize and check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.subplots(3, 3, figsize=(8, 8))\n",
    "for i, k in enumerate(np.random.randint(num_total, size=9)):\n",
    "    im = PIL.Image.open(image_files_list[k])\n",
    "    arr = np.array(im)\n",
    "    plt.subplot(3, 3, i + 1)\n",
    "    plt.xlabel(class_names[image_class[k]])\n",
    "    plt.imshow(arr, cmap=\"gray\", vmin=0, vmax=255)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare training, validation and test data lists\n",
    "\n",
    "Randomly select 10% of the dataset as validation and 10% as test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Training count: 47156, Validation count: 5913, Test count: 5885\n"
    }
   ],
   "source": [
    "val_frac = 0.1\n",
    "test_frac = 0.1\n",
    "train_x = list()\n",
    "train_y = list()\n",
    "val_x = list()\n",
    "val_y = list()\n",
    "test_x = list()\n",
    "test_y = list()\n",
    "\n",
    "for i in range(num_total):\n",
    "    rann = np.random.random()\n",
    "    if rann < val_frac:\n",
    "        val_x.append(image_files_list[i])\n",
    "        val_y.append(image_class[i])\n",
    "    elif rann < test_frac + val_frac:\n",
    "        test_x.append(image_files_list[i])\n",
    "        test_y.append(image_class[i])\n",
    "    else:\n",
    "        train_x.append(image_files_list[i])\n",
    "        train_y.append(image_class[i])\n",
    "\n",
    "print(f\"Training count: {len(train_x)}, Validation count: {len(val_x)}, Test count: {len(test_x)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define MONAI transforms, Dataset and Dataloader to pre-process data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_transforms = Compose(\n",
    "    [\n",
    "        LoadPNG(image_only=True),\n",
    "        AddChannel(),\n",
    "        ScaleIntensity(),\n",
    "        RandRotate(range_x=15, prob=0.5, keep_size=True),\n",
    "        RandFlip(spatial_axis=0, prob=0.5),\n",
    "        RandZoom(min_zoom=0.9, max_zoom=1.1, prob=0.5),\n",
    "        ToTensor(),\n",
    "    ]\n",
    ")\n",
    "\n",
    "val_transforms = Compose([LoadPNG(image_only=True), AddChannel(), ScaleIntensity(), ToTensor()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MedNISTDataset(torch.utils.data.Dataset):\n",
    "    def __init__(self, image_files, labels, transforms):\n",
    "        self.image_files = image_files\n",
    "        self.labels = labels\n",
    "        self.transforms = transforms\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.image_files)\n",
    "\n",
    "    def __getitem__(self, index):\n",
    "        return self.transforms(self.image_files[index]), self.labels[index]\n",
    "\n",
    "\n",
    "train_ds = MedNISTDataset(train_x, train_y, train_transforms)\n",
    "train_loader = torch.utils.data.DataLoader(train_ds, batch_size=300, shuffle=True, num_workers=10)\n",
    "\n",
    "val_ds = MedNISTDataset(val_x, val_y, val_transforms)\n",
    "val_loader = torch.utils.data.DataLoader(val_ds, batch_size=300, num_workers=10)\n",
    "\n",
    "test_ds = MedNISTDataset(test_x, test_y, val_transforms)\n",
    "test_loader = torch.utils.data.DataLoader(test_ds, batch_size=300, num_workers=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define network and optimizer\n",
    "\n",
    "1. Set learning rate for how much the model is updated per batch.\n",
    "1. Set total epoch number, as we have shuffle and random transforms, so the training data of every epoch is different.  \n",
    "And as this is just a get start tutorial, let's just train 4 epochs.  \n",
    "If train 10 epochs, the model can achieve 100% accuracy on test dataset.\n",
    "1. Use DenseNet from MONAI and move to GPU devide, this DenseNet can support both 2D and 3D classification tasks.\n",
    "1. Use Adam optimizer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "device = torch.device(\"cuda:0\")\n",
    "model = densenet121(spatial_dims=2, in_channels=1, out_channels=num_class).to(device)\n",
    "loss_function = torch.nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), 1e-5)\n",
    "epoch_num = 4\n",
    "val_interval = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model training\n",
    "\n",
    "Execute a typical PyTorch training that run epoch loop and step loop, and do validation after every epoch.  \n",
    "Will save the model weights to file if got best validation accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "train completed, best_metric: 1.0000 at epoch: 4\n"
    }
   ],
   "source": [
    "best_metric = -1\n",
    "best_metric_epoch = -1\n",
    "epoch_loss_values = list()\n",
    "metric_values = list()\n",
    "\n",
    "for epoch in range(epoch_num):\n",
    "    print(\"-\" * 10)\n",
    "    print(f\"epoch {epoch + 1}/{epoch_num}\")\n",
    "    model.train()\n",
    "    epoch_loss = 0\n",
    "    step = 0\n",
    "    for batch_data in train_loader:\n",
    "        step += 1\n",
    "        inputs, labels = batch_data[0].to(device), batch_data[1].to(device)\n",
    "        optimizer.zero_grad()\n",
    "        outputs = model(inputs)\n",
    "        loss = loss_function(outputs, labels)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        epoch_loss += loss.item()\n",
    "        print(f\"{step}/{len(train_ds) // train_loader.batch_size}, train_loss: {loss.item():.4f}\")\n",
    "        epoch_len = len(train_ds) // train_loader.batch_size\n",
    "    epoch_loss /= step\n",
    "    epoch_loss_values.append(epoch_loss)\n",
    "    print(f\"epoch {epoch + 1} average loss: {epoch_loss:.4f}\")\n",
    "\n",
    "    if (epoch + 1) % val_interval == 0:\n",
    "        model.eval()\n",
    "        with torch.no_grad():\n",
    "            y_pred = torch.tensor([], dtype=torch.float32, device=device)\n",
    "            y = torch.tensor([], dtype=torch.long, device=device)\n",
    "            for val_data in val_loader:\n",
    "                val_images, val_labels = (\n",
    "                    val_data[0].to(device),\n",
    "                    val_data[1].to(device),\n",
    "                )\n",
    "                y_pred = torch.cat([y_pred, model(val_images)], dim=0)\n",
    "                y = torch.cat([y, val_labels], dim=0)\n",
    "            auc_metric = compute_roc_auc(y_pred, y, to_onehot_y=True, softmax=True)\n",
    "            metric_values.append(auc_metric)\n",
    "            acc_value = torch.eq(y_pred.argmax(dim=1), y)\n",
    "            acc_metric = acc_value.sum().item() / len(acc_value)\n",
    "            if auc_metric > best_metric:\n",
    "                best_metric = auc_metric\n",
    "                best_metric_epoch = epoch + 1\n",
    "                torch.save(model.state_dict(), os.path.join(root_dir, \"best_metric_model.pth\"))\n",
    "                print(\"saved new best metric model\")\n",
    "            print(\n",
    "                f\"current epoch: {epoch + 1} current AUC: {auc_metric:.4f}\"\n",
    "                f\" current accuracy: {acc_metric:.4f} best AUC: {best_metric:.4f}\"\n",
    "                f\" at epoch: {best_metric_epoch}\"\n",
    "            )\n",
    "\n",
    "        IPython.display.clear_output()\n",
    "\n",
    "print(f\"train completed, best_metric: {best_metric:.4f} at epoch: {best_metric_epoch}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the loss and metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure(\"train\", (12, 6))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.title(\"Epoch Average Loss\")\n",
    "x = [i + 1 for i in range(len(epoch_loss_values))]\n",
    "y = epoch_loss_values\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.plot(x, y)\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.title(\"Val AUC\")\n",
    "x = [val_interval * (i + 1) for i in range(len(metric_values))]\n",
    "y = metric_values\n",
    "plt.xlabel(\"epoch\")\n",
    "plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate the model on test dataset\n",
    "\n",
    "After training and validation, we already got the best model on validation test.  \n",
    "We need to evaluate the model on test dataset to check whether it's robust and not over-fitting.  \n",
    "We'll use these predictions to generate a classification report."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.load_state_dict(torch.load(os.path.join(root_dir, \"best_metric_model.pth\")))\n",
    "model.eval()\n",
    "y_true = list()\n",
    "y_pred = list()\n",
    "with torch.no_grad():\n",
    "    for test_data in test_loader:\n",
    "        test_images, test_labels = (\n",
    "            test_data[0].to(device),\n",
    "            test_data[1].to(device),\n",
    "        )\n",
    "        pred = model(test_images).argmax(dim=1)\n",
    "        for i in range(len(pred)):\n",
    "            y_true.append(test_labels[i].item())\n",
    "            y_pred.append(pred[i].item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "%pip install -qU sklearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "precision    recall  f1-score   support\n\n   AbdomenCT     0.9827    0.9938    0.9882       969\n   BreastMRI     0.9979    0.9894    0.9936       944\n         CXR     0.9979    0.9928    0.9954       973\n     ChestCT     0.9958    1.0000    0.9979       959\n        Hand     0.9943    0.9943    0.9943      1055\n      HeadCT     0.9959    0.9939    0.9949       985\n\n    accuracy                         0.9941      5885\n   macro avg     0.9941    0.9940    0.9941      5885\nweighted avg     0.9941    0.9941    0.9941      5885\n\n"
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print(classification_report(y_true, y_pred, target_names=class_names, digits=4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleanup data directory\n",
    "\n",
    "Remove directory if a temporary was used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "if directory is None:\n",
    "    shutil.rmtree(root_dir)"
   ]
  }
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